Investigating the attainment of optimum data quality for EHR Big Data: proposing a new methodological approach
PhD thesis
Juddoo, S. 2022. Investigating the attainment of optimum data quality for EHR Big Data: proposing a new methodological approach. PhD thesis Middlesex University Computer Science
Type | PhD thesis |
---|---|
Title | Investigating the attainment of optimum data quality for EHR Big Data: proposing a new methodological approach |
Authors | Juddoo, S. |
Abstract | The value derivable from the use of data is continuously increasing since some years. Both commercial and non-commercial organisations have realised the immense benefits that might be derived if all data at their disposal could be analysed and form the basis of decision taking. The technological tools required to produce, capture, store, transmit and analyse huge amounts of data form the background to the development of the phenomenon of Big Data. With Big Data, the aim is to be able to generate value from huge amounts of data, often in non-structured format and produced extremely frequently. However, the potential value derivable depends on general level of governance of data, more precisely on the quality of the data. The field of data quality is well researched for traditional data uses but is still in its infancy for the Big Data context. This dissertation focused on investigating effective methods to enhance data quality for Big Data. The principal deliverable of this research is in the form of a methodological approach which can be used to optimize the level of data quality in the Big Data context. Since data quality is contextual, (that is a non-generalizable field), this research study focuses on applying the methodological approach in one use case, in terms of the Electronic Health Records (EHR). |
Sustainable Development Goals | 9 Industry, innovation and infrastructure |
Middlesex University Theme | Creativity, Culture & Enterprise |
Department name | Computer Science |
Institution name | Middlesex University |
Publication dates | |
06 Jan 2023 | |
Publication process dates | |
Deposited | 06 Jan 2023 |
Accepted | 23 May 2022 |
Output status | Published |
Accepted author manuscript | |
Language | English |
https://repository.mdx.ac.uk/item/8q372
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